Imagine you’ve created a machine learning model and are eager to share it with others. Consider the following scenarios for sharing your model:
https://cpsc330-moment-predictor.onrender.com/
https://canvas.ubc.ca/courses/170662/external_tools/53187
Part 1: Supervised learning on tabular data: ML fundamentals, preprocessing and data encoding, a bunch of models, evaluation metrics, feature importances and model transparency, feature selection, hyperparameter optimization
Part 2: Dealing with other non-tabular data types: Clustering, recommender systems, computer vision with pre-trained deep learning models (high level), language data, text preprocessing, embeddings, topic modeling, time series, right-censored data / survival analysis
Part 3: Communication, Ethics, and Deployment
If you want to further develop your machine learning skills:
Practice!
Work on your own projects. Make your work available and reproducible.
If you are interested in research in machine learning
For each of the scenarios below
| App | Goal |
|---|---|
| QueuePredictor app | Inform callers how long they’ll wait on hold given the current call volume |
| To-doList App | Keep track of the tasks that a user inputs and organize them by date |
| SegmentSphere App | To segment customers to tailor marketing strategies based on purchasing behavior |
| Video app | Recommend useful videos |
| Dining app | Identify cuisine by a restaurant’s menu |
| Weather app | Calculate precipitation in six hour increments for a geographic region |
| EvoCarShare app | Calculate number of car rentals in four increaments at a particular Evo parking spot |
| Pharma app | Understand the effect of a new drug on patient survival time |
That’s all! We made it! I hope you learned something useful from the course. You all are wonderful students and I had fun teaching this course ♥️!

If you didn’t fill out course evaluations during class , it’ll be great if you can fill them in when you get a chance.